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为了高值化综合开发裂殖壶藻，以未破壁的裂殖壶藻粉为原料，优化三相分离（TPP）法联产提取裂殖壶藻中油脂、蛋白质和多糖的工艺。结果表明，采用TPP法联产提取裂殖壶藻中油脂、蛋白质和多糖的最佳条件为悬浮液中硫酸铵质量浓度5 g/15 mL，叔丁醇与悬浮液体积比3∶ 1，液料比120∶ 1。在上述优化的条件下，TPP法提取裂殖壶藻油脂的最佳提取温度和提取时间分别为90 ℃和3 h，提取蛋白质和多糖的最佳提取温度和提取时间分别为60 ℃和0.5 h。此外，评估不同策略下TPP法联产提取裂殖壶藻油脂、蛋白质和多糖的性能发现，先在60 ℃下提取0.5 h再在90 ℃下提取3 h，总油脂、蛋白质和多糖提取率最高，分别达97.86%、57.11%和28.15%，油脂中DHA含量可达35.30%，DPA含量可达5.53%。综上，TPP法是一种高效联产提取裂殖壶藻中油脂、蛋白质和多糖的方法。 In order to the comprehensive development of Schizochytrium sp. with high value, the process of the simultaneous extraction of oil, protein and polysaccharide from the unbroken Schizochytrium sp. by three phase partitioning (TPP) method were optimized. The results showed that the optimal conditions for the simultaneous extraction of oil, protein and polysaccharide from Schizochytrium sp. by TPP method were as follows: mass concentration of ammonium sulfate in suspension 5 g/15 mL, volume ratio of t-butanol to suspension 3∶ 1, ratio of total volume to algal powder mass 120∶ 1. Under the optimized conditions, the optimal extraction temperature and time of lipids from Schizochytrium sp. by TPP method were 90 ℃ and 3 h, respectively, and the optimal extraction temperature and time of protein and polysaccharide were 60 ℃ and 0.5 h, respectively. Moreover, the extraction performance of TPP method to simultaneously extract the lipids, protein and polysaccharide from Schizochytrium sp. was further evaluated by different strategies. It was found that the extraction at 60 ℃ for 0.5 h followed by 90 ℃ for 3 h resulted in the highest extraction rates of 97.86%, 57.11% and 28.15% for total lipids, protein and polysaccharide, respectively, with DHA content up to 35.30% and DPA content up to 5.53% in the lipids. In conclusion, the TPP method is a highly efficient method for simultaneously extracting lipids, protein and polysaccharide from Schizochytrium sp.

Copyright of Paint & Coatings Industry (0253-4312) is the property of Paint & Coatings Industry Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

多不饱和脂肪酸是一类对人体健康有益的生物活性物质，微藻油脂富含多不饱和脂肪酸，是天然可食用的潜在油源。利用微藻油脂开发制备型功能性油脂，替代动植物天然功能性油脂，不仅可提高天然功能性油脂的品质，解决供应问题，而且有望得到新的功能性油脂制品。对酶法制备功能性油脂的方法、常见微藻的油脂含量及其油脂的脂肪酸组成进行综述，并对酶法改性微藻油脂制备富含多不饱和脂肪酸的单酰甘油酯、结构三酰甘油酯、功能性磷脂等功能性油脂的研究进展进行了介绍。酶法改性微藻油脂制备功能性油脂是高值化利用微藻油脂的新途径。 Polyunsaturated fatty acids (PUFAs) are health-beneficial bioactive compounds. Microalgal oils are natural and edible potential bioresources rich in PUFAs. Using microalgal oils to produce prepared functional lipids to replace natural animal and vegetable functional lipids not only can solve the bottleneck in the quality and supply for natural functional lipids, but also hopefully obtain new functional lipids products.The preparation of functional lipids by enzymatic method, lipid content and fatty acid composition of common microalgae were summarized, and the research progress on the preparation of functional lipids such as monoglycerides, structural triacylglycerides and functional phospholipid rich in PUFAs by enzymatic modification of microalgal oil was introduced. Preparation of functional lipids by enzymatic modification of microalgal oil is an new way for high-value utilization of microalgal oil.

Copyright of Journal of Hydrobiology / Shuisheng Shengwu Xuebao is the property of Editorial Department of Journal of Hydrobiology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

[Significance] With the rapid development of robotics technology and the persistently rise of labor costs, the application of robots in facility agriculture is becoming increasingly widespread. These robots can enhance operational efficiency, reduce labor costs, and minimize human errors. However, the complexity and diversity of facility environments, including varying crop layouts and lighting conditions, impose higher demands on robot navigation. Therefore, achieving stable, accurate, and rapid navigation for robots has become a key issue. Advanced sensor technologies and algorithms have been proposed to enhance robots' adaptability and decision-making capabilities in dynamic environments. This not only elevates the automation level of agricultural production but also contributes to more intelligent agricultural management. [Progress] This paper reviews the key technologies of automatic navigation for facility agricultural robots. It details beacon localization, inertial positioning, simultaneous localization and mapping (SLAM) techniques, and sensor fusion methods used in autonomous localization and mapping. Depending on the type of sensors employed, SLAM technology could be subdivided into vision-based, laser-based and fusion systems. Fusion localization is further categorized into data-level, feature-level, and decision-level based on the types and stages of the fused information. The application of SLAM technology and fusion localization in facility agriculture has been increasingly common. Global path planning plays a crucial role in enhancing the operational efficiency and safety of facility aricultural robots. This paper discusses global path planning, classifying it into point-to-point local path planning and global traversal path planning. Furthermore, based on the number of optimization objectives, it was divided into single-objective path planning and multiobjective path planning. In regard to automatic obstacle avoidance technology for robots, the paper discusses sevelral commonly used obstacle avoidance control algorithms commonly used in facility agriculture, including artificial potential field, dynamic window approach and deep learning method. Among them, deep learning methods are often employed for perception and decision-making in obstacle avoidance scenarios. [Conclusions and Prospects] Currently, the challenges for facility agricultural robot navigation include complex scenarios with significant occlusions, cost constraints, low operational efficiency and the lack of standardized platforms and public datasets. These issues not only affect the practical application effectiveness of robots but also constrain the further advancement of the industry. To address these challenges, future research can focus on developing multi-sensor fusion technologies, applying and optimizing advanced algorithms, investigating and implementing multi-robot collaborative operations and establishing standardized and shared data platforms. [ABSTRACT FROM AUTHOR]

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Objective：To screen the aging genes closely associated with pelvic organ prolapse (POP) by bioinformatics techniques, and to clarify the potential clinical significance and value of key genes. Methods：Gene Expression Omnibus (GEO) Database was used to download the datasets GSE53868 and GSE151188 for POP-related genes with the keyword “pelvic organ prolapse”. The aging-related genes were obtained from Aging Atlas, CellAge, and the Human Ageing Genomic Resources (HAGR) Databases；the intersection of genes related with POP in two groups provided a list of differentially expressed genes (DEGs) associated with aging in POP； gene Set Enrichment Analysis (GSEA) was conducted with R software version 4. 2. 1； Gene Ontology (GO) functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway enrichment analysis of DEGs were conducted by the Database for Annotation, Visualization and Integrated Discovery (DAVID) ； the proteinprotein interaction (PPI) network was constructed with Cytoscape 3. 9. 1 software；the top 10 Hub genes were selected by cytoHubba plugin； the infiltration of 22 types of immune cells in the patients in POP group and control group was analyzed by CIBERSORT deconvolution method using R software；the key genes were further screened by LASSO regression algorithm； the correlation and diagnostic efficacy between key genes and immune cell infiltration were analyzed. Results：From the Aging Atlas, CellAge, and HAGR Databases，724 aging-related genes were identified. Intersection with the POP expression profile yielded an aging gene expression matrix related to POP containing 624 genes, and 29 POP-related DEGs were identified after differential analysis, including 2 upregulated genes and 27 downregulated genes. The GSEA results showed that the upregulated pathways were mainly related to diabetes and cellular senescence, whereas the downregulated pathways included Alzheimer’s disease and hypoxia-inducible factor-1 (HIF-1) signaling pathways. The GO functional enrichment analysis mainly enriched in the biological processes such as the response of the cells to lipopolysaccharide, inflammatory response, and negative regulation of cell proliferation. The KEGG signaling pathway enrichment analysis mainly enriched in interleukin-17 (IL-17), tumor necrosis factor (TNF), and nuclear factor-kappa B (NF-κB) signaling pathways. The PPI network analysis got 10 Hub genes including interleukin-6 (IL-6), interleukin-1B (IL-1B), prostaglandinendoperoxide synthase 2 (PTGS2), and NF-kappa-B inhibitor alpha (NFKBIA) . The CIBERSORT deconvolution method results showed a relatively higher infiltration proportion of neutrophils and activated mast cells in the patients in POP group, the activated mast cells had a positive correlation with most of the DEGs (r>0. 5) and the macrophages had a significant positive correlation with IL-1B (r>0. 6) . The key genes Jun D proto-oncogene (JUND), Snail homolog 1 (SNAI1), amphiregulin (AREG), Lamin A/C (LMNA), and superoxide dismutase 2 (SOD2) selected by LASSO regression analysis had high diagnostic efficacies, and the area under receiver operating characteristic curve (ROC) (AUC) were all greater than 0. 75. Conclusion During the aging process, the genes such as JUND, SNAI1, AREG, LMNA, and SOD2 may participate in the pathophysiology of POP through various pathways, including inflammation-related pathways, transcription regulation, and affecting collagen secretion and metabolism, thereby influence the connective tissue support function and promote the occurrence and development of POP. [ABSTRACT FROM AUTHOR]

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2012年1月13日～5月8日,采用瞬时扫描法、全事件取样法及目标取样法对昆明动物园4只圈养大象(3♀1♂)的昼间行为时间分配及活动节律进行了观察与分析。结果表明:圈养亚洲象在取食行为、运动行为、站立行为、休息行为、交往行为、情绪行为和其他行为中主要以取食和运动2类行为为主,除怀孕象运动(14%)少于取食(67%)外,其余都是运动行为时间分配大于取食行为时间分配,其他行为分配时间均不超过10%。在工作日和节假日雄象的运动行为和取食行为大致相似,而雌象表现为在工作日的运动行为多于节假日,取食行为则相反; 取食行为上雌、雄象分别在10:00～11:00、14:00～15:00和11:00～12:00、14:00～15:00出现2个明显的波峰,而运动行为上雌、雄象在13:00～14:00都形成一个明显的波峰,在14:00～15:00都形成一个显著的波谷,其余行为雌、雄节律性不明显。综合分析发现雌、雄象的昼间活动规律在10:00～11:00至13:00～14:00表现出一定的差异,其余时间行为基本相似,且用Mann-Whitney U Test分析差异不显著(Z=-1.619,P>0.05)。

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The experiment was to determine the chemical components of different parts of Tartary buckwheat. The chemical constituents of different parts of tartary buckwheat were detected by liquid chromatograph, to analyze the qualitative and quantitative analysis of test results. The results showed that a total of 30 active substances and 19 trace elements were detected from the leaves, stems and roots of tartary buckwheat. The study indicates that the plant of tartary buckwheat contains valuable traditional Chinese medicine ingredients and relatively rich trace elements, which can be used for the development of traditional Chinese medicine and health feed to reduce the addition of antibiotics in feed. [ABSTRACT FROM AUTHOR]

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Accurate acquisition of crop information is very important for the real-time monitoring of crop growth status in crop breeding and agricultural precision management. The ever-increasing remote sensing (RS) and Unmanned Aerial vehicles (UAV) have been widely used to collect the big phenotypic data (especially image data) of various plants in a large area. Specific sensing devices are often used to obtain accurate and comprehensive information on crop growth. However, the diversity of sensing devices can bring a great challenge to the cooperation between them on UAV. It is very urgent to establish UAV flight parameters suitable for the complex field environment. In this study, an effective approach was developed to explore the effects of UAV flight height on the estimated fractional vegetation cover (FVC) and vegetation index (VI). The UAV can ultimately be utilized to collect the phenotypic data within the effective range under the multi-sensor combinations based on suitable flight height. The multispectral and high-resolution RGB cameras were simultaneously mounted on the UAV to acquire the images at a speed of 2.5 m/s. Among them, the heading and the side overlaps were set as 75% and 60%, respectively, particularly for the possibility of successful image stitching. The initial flight heights were set as 25 and 50 m, in order to exclude the wind field generated by the high-speed rotation of the UAV's paddles from disturbing the crop. The high ground resolution (GR) images were collected by the UAV at the low flight height. These images were then degraded by image processing into a series of images with different GR. The simulation was finally carried out to predict the crop images obtained by the UAV at different flight heights. As such, the impact of environmental changes on image quality was reduced, such as the light intensity. The FVC of every sample plot was estimated using Random Forest (RF). The results show that the vegetation classification accuracy was greater than 91%. The regular FVC changes were found in the different GR, due to the image blending phenomenon. Once the FVC was less than half, the indicator was constantly underestimated with the decrease of the GR. Otherwise, the indicator was overestimated. Pearson correlation analysis was also performed on the real and simulated images at a flight height of 50 m, in order to verify the feasibility of simulated images for FVC estimation. The results show that the Pearson correlation coefficient was 0.992 8 between the real and simulated images at a flight height of 50 m, indicating a high correlation. Moreover, a similar regular variation was also found in the FVC that was estimated by the real images. Five VIs (the combination of spectral reflectance) were calculated to enhance vegetation information and weaken non-vegetation one. The hypothesis testing was used to verify whether the vegetation indices had significant differences. The results show that significant differences (P<0.05) occurred in the RGB VIs at a ground resolution of 15 mm/pixel (i.e., the flight height of 61 m), whereas no difference (P>0.1) was found at 10 mm/pixel (i.e., flight height of 42 m). Meanwhile, the multispectral VIs were not significantly different at both ground resolutions (P>0.5). Fortunately, the flight height range within 42 m presented less impact on the acquisition of RGB spectral information. Consequently, a flight height of less than 42 m can be the optimal parameter to collect the crop information using the two devices at the same time. Anyway, the spectral and spatial information using other devices at higher flight heights can also be further investigated in the future. The finding can provide a strong reference for setting the suitable flight height to obtain the crop information, in order to reduce the operating costs using multi-sensor equipment carried by UAVs. [ABSTRACT FROM AUTHOR]

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